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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">cardiovascular</journal-id><journal-title-group><journal-title xml:lang="ru">Кардиоваскулярная терапия и профилактика</journal-title><trans-title-group xml:lang="en"><trans-title>Cardiovascular Therapy and Prevention</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1728-8800</issn><issn pub-type="epub">2619-0125</issn><publisher><publisher-name>«SILICEA-POLIGRAF» LLC</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.15829/1728-8800-2023-3698</article-id><article-id custom-type="edn" pub-id-type="custom">QWCCQD</article-id><article-id custom-type="elpub" pub-id-type="custom">cardiovascular-3698</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>АТЕРОСКЛЕРОЗ КОРОНАРНЫХ АРТЕРИЙ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>CORONARY ARTERY ATHEROSCLEROSIS</subject></subj-group></article-categories><title-group><article-title>Разработка алгоритма неинвазивной диагностики стенозирующего атеросклероза коронарных артерий на основе визуализирующих и лабораторных маркеров</article-title><trans-title-group xml:lang="en"><trans-title>Algorithm for non-invasive diagnosis of obliterating coronary atherosclerosis based on imaging and laboratory markers</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-4453-8430</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Драпкина</surname><given-names>О. М.</given-names></name><name name-style="western" xml:lang="en"><surname>Drapkina</surname><given-names>O. M.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Драпкина Оксана Михайловна — доктор медицинских наук, профессор, академик РАН, директор</p><p>Москва</p></bio><bio xml:lang="en"><p>Moscow</p></bio><email xlink:type="simple">cardiovasc.journal-1@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-8665-9129</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Метельская</surname><given-names>В. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Metelskaya</surname><given-names>V. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Доктор биологических наук, профессор, главный научный сотрудник, руководитель отдела биохимических маркеров риска хронических неинфекционных заболеваний, профессор кафедры клинической лабораторной диагностики</p><p>Москва</p></bio><bio xml:lang="en"><p>Moscow</p></bio><email xlink:type="simple">vametelskaya@gmail.com</email><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-9991-1063</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Дубинская</surname><given-names>М. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Dubinskaya</surname><given-names>M. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Кандидат медицинских наук, врач-кардиолог отделения для пациентов с острым инфарктом миокарда</p><p>Москва</p></bio><bio xml:lang="en"><p>Moscow</p></bio><email xlink:type="simple">cardiovasc.journal-1@yandex.ru</email><xref ref-type="aff" rid="aff-3"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-6615-4315</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Яровая</surname><given-names>Е. Б.</given-names></name><name name-style="western" xml:lang="en"><surname>Yarovaya</surname><given-names>E. B.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Доктор физико-математических наук, профессор, руководитель лаборатории биостатистики отдела эпидемиологии хронических неинфекционных заболеваний, профессор кафедры теории вероятностей механико-математического факультета</p><p>Москва</p></bio><bio xml:lang="en"><p>Moscow</p></bio><email xlink:type="simple">cardiovasc.journal-1@yandex.ru</email><xref ref-type="aff" rid="aff-4"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ФГБУ "Национальный медицинский исследовательский центр терапии и профилактической медицины" Минздрава России</institution></aff><aff xml:lang="en"><institution>National Medical Research Center for Therapy and Preventive Medicine</institution></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>ФГБУ "Национальный медицинский исследовательский центр терапии и профилактической медицины" Минздрава России;&#13;
ФГБУ "Российская медицинская академия непрерывного профессионального образования" Минздрава России</institution></aff><aff xml:lang="en"><institution>National Medical Research Center for Therapy and Preventive Medicine;&#13;
Russian Medical Academy of Continuous Professional Education</institution></aff></aff-alternatives><aff-alternatives id="aff-3"><aff xml:lang="ru"><institution>ГБУЗ города Москвы "ГКБ №15 им. О. М. Филатова ДЗМ"</institution></aff><aff xml:lang="en"><institution>Filatov City Clinical Hospital № 15</institution></aff></aff-alternatives><aff-alternatives id="aff-4"><aff xml:lang="ru"><institution>ФГБУ "Национальный медицинский исследовательский центр терапии и профилактической медицины" Минздрава России;&#13;
ФГБОУ ВО "Московский государственный университет им. М. В. Ломоносова"</institution></aff><aff xml:lang="en"><institution>National Medical Research Center for Therapy and Preventive Medicine;&#13;
Lomonosov Moscow State University</institution></aff></aff-alternatives><pub-date pub-type="collection"><year>2023</year></pub-date><pub-date pub-type="epub"><day>23</day><month>08</month><year>2023</year></pub-date><volume>22</volume><issue>8</issue><fpage>3698</fpage><lpage>3698</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Драпкина О.М., Метельская В.А., Дубинская М.В., Яровая Е.Б., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Драпкина О.М., Метельская В.А., Дубинская М.В., Яровая Е.Б.</copyright-holder><copyright-holder xml:lang="en">Drapkina O.M., Metelskaya V.A., Dubinskaya M.V., Yarovaya E.B.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://cardiovascular.elpub.ru/jour/article/view/3698">https://cardiovascular.elpub.ru/jour/article/view/3698</self-uri><abstract><sec><title>Цель</title><p>Цель. С использованием ультразвуковых характеристик сонных и бедренных артерий и ряда лабораторных показателей крови разработать алгоритм неинвазивной диагностики атеросклероза коронарных артерий (КА).</p></sec><sec><title>Материал и методы</title><p>Материал и методы. Обследовано 216 пациентов (53% мужчин) в возрасте 24-87 лет (средний возраст 61,5±10,73 лет), поступивших и обследованных в стационаре ФГБУ "НМИЦ ТПМ" Минздрава России в период 2016-2019гг. Всем пациентам была выполнена диагностическая коронароангиография, дуплексное сканирование сонных и бедренных артерий, определен широкий спектр биохимических показателей крови. В соответствии с данными коронароангиографии были сформированы 3 группы пациентов: 1) с отсутствием атеросклероза КА, 2) с субклиническим и 3) с выраженным коронарным атеросклерозом, результаты обследования которых легли в основу разработанного диагностического алгоритма.</p></sec><sec><title>Результаты</title><p>Результаты. Разработан ступенчатый алгоритм неинвазивной детекции коронарного атеросклероза, который включает биохимические показатели крови на I ступени (глюкоза, высокочувствительный С-реактивный белок, креатинин и адипонектин), визуальную шкалу (ВШ) на II ступени, сочетание клинико-­инструментальных параметров (проба Целермайера и переднезадний размер левого предсердия) на III ступени и позволяет выявлять пациентов с разной степенью коронарного поражения (включая субклиническое). Последовательное прохождение пациентом ступеней алгоритма увеличивает шанс выявления атеросклероза КА любой степени в 12,2 раза, а выраженного в 13,8 раз.</p></sec><sec><title>Заключение</title><p>Заключение. Для обоснования предложения по использованию комбинированной панели рутинно доступных клинико-­инструментальных исследований и анализов крови, представленной в виде ступенчатого диагностического алгоритма, целесообразно провести валидацию предложенного алгоритма на независимой когорте или при проспективном наблюдении за исходной когортой пациентов.</p></sec></abstract><trans-abstract xml:lang="en"><sec><title>Aim</title><p>Aim. Using the ultrasound characteristics of the carotid and femoral arteries and a number of laboratory blood parameters, develop an algorithm for non-invasive diagnosis of coronary atherosclerosis.</p></sec><sec><title>Material and methods</title><p>Material and methods. The study included 216 patients (53% men) aged 24-87 years (mean age, 61,5±10,73 years) who were admitted and examined in the hospital of the National Medical Research Center for Therapy and Preventive Medicine in the period of 2016-2019. All patients underwent diagnostic coronary angiography, duplex carotid and femoral ultrasound and biochemical blood tests. In accordance with coronary angiography, 3 groups of patients were formed: 1) without coronary atherosclerosis, 2) with subclinical and 3) severe coronary atherosclerosis, the examination results of which formed the basis of the developed diagnostic algorithm.</p></sec><sec><title>Results</title><p>Results. A stepwise algorithm for non-invasive detection of coronary atherosclerosis has been developed, which includes biochemical blood tests at stage I (glucose, high-sensitivity C-reactive protein, creatinine and adiponectin), a visual scale (VS) at stage II, a combination of clinical and paraclinical parameters (Celermajer test and left atrium antero-­posterior diameter) at stage III and allows to identify patients with varying degrees of coronary onvolvement (including subclinical). The sequential passage of algorithm steps by the patient increases the detection rate of coronary atherosclerosis of any degree by 12,2 times, and by 13,8 times in case of severe involvement.</p></sec><sec><title>Conclusion</title><p>Conclusion. To rationale the use of a combined panel of available investigations, presented as a stepwise diagnostic algorithm, the proposed algorithm should be validated on an independent cohort or in prospective observation of the initial cohort of patients.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>алгоритм диагностический</kwd><kwd>атеросклероз</kwd><kwd>коронарные</kwd><kwd>сонные и бедренные артерии</kwd><kwd>биохимические показатели</kwd><kwd>визуализирующие показатели</kwd><kwd>математические модели</kwd></kwd-group><kwd-group xml:lang="en"><kwd>diagnostic algorithm</kwd><kwd>atherosclerosis</kwd><kwd>coronary</kwd><kwd>carotid and femoral arteries</kwd><kwd>biochemical parameters</kwd><kwd>imaging parameters</kwd><kwd>mathematical models</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">McNamara K, Alzubaidi C, Jackson JK. 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